As treatment of the early, inflammatory phase of sepsis improves, post-sepsis immunosuppression and secondary infection have increased in importance. How early inflammation drives immunosuppression remains unclear. Although IFN-γ typically helps microbial clearance, we found that increased plasma IFN-γ in early clinical sepsis was associated with the later development of secondary Candida infection. Consistent with this observation, we found that exogenous IFN-γ suppressed macrophage phagocytosis of zymosan in vivo, and antibody blockade of IFN-γ after endotoxemia improved survival of secondary candidemia. Transcriptomic analysis of innate lymphocytes during endotoxemia suggested that NKT cells drove IFN-γ production by NK cells via mTORC1. Activation of invariant NKT (iNKT) cells with glycolipid antigen drove immunosuppression. Deletion of iNKT cells in Cd1d–/– mice or inhibition of mTOR by rapamycin reduced immunosuppression and susceptibility to secondary Candida infection. Thus, although rapamycin is typically an immunosuppressive medication, in the context of sepsis, rapamycin has the opposite effect. These results implicated an NKT cell/mTOR/IFN-γ axis in immunosuppression following endotoxemia or sepsis. In summary, in vivo iNKT cells activated mTORC1 in NK cells to produce IFN-γ, which worsened macrophage phagocytosis, clearance of secondary Candida infection, and mortality.
Edy Y. Kim, Hadas Ner-Gaon, Jack Varon, Aidan M. Cullen, Jingyu Guo, Jiyoung Choi, Diana Barragan-Bradford, Angelica Higuera, Mayra Pinilla-Vera, Samuel A.P. Short, Antonio Arciniegas-Rubio, Tomoyoshi Tamura, David E. Leaf, Rebecca M. Baron, Tal Shay, Michael B. Brenner
Usage data is cumulative from February 2024 through February 2025.
Usage | JCI | PMC |
---|---|---|
Text version | 1,114 | 275 |
119 | 123 | |
Figure | 246 | 8 |
Table | 83 | 0 |
Supplemental data | 49 | 1 |
Citation downloads | 59 | 0 |
Totals | 1,670 | 407 |
Total Views | 2,077 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.